1. Introduction to Xinformatics: Course Scope, Assessments
Peter Fox
Xinformatics
ITWS, ERTH, CSCI 4400/6400
Module 1, January 16, 2018

2. Contents Introductions Course Outline Application areas
Logistics and resources
Assessment and assignments
Learning objectives, outcomes
Introduction to Xinformatics
Discussion
Next modules and classes

3. E-Introductions Post a message to LMS Discussion Boards
Name, major, year
This course: Interest, goals, outcomes?
Have you completed any *suggested* prerequisites:
Knowledge such as that gained in a Data Base class (e.g., CSCI-4380)
Knowledge such as that gained in a Data Structures class (e.g., CSCI-1200)
Knowledge such as that gained in a Data Science class (e.g. ITEC/CSCI/ERTH 4350/6350)

4. Course Outline Introduction to Informatics
Capturing the problem: Use case development and requirement analysis
Information theory, models, tools
Foundations; semiotics, library, cognitive and social science
State-of-the-Art, informatics applications
Information life-cycle
Information architectures (Internet, Web, Grid, Cloud)
Information Visualization, Information Discovery, Information Integration
Information Audit and Workflow
Information quality, and bias
Class exercises, guest lectures and current events along the way

5. Application Areas Geoinformatics Astroinformatics Cheminformatics
Bioinformatics
Helioinformatics
Healthinformatics
Ecoinformatics
Nursing informatics
and the list goes on, and on

6. Logistics
Class: ITWS, ERTH, CSCI 4400/6400, Hours: 3:00pm-5:50pm Tuesdays
Location: Lally 102
Instructors:
Peter Fox,
Office Hours: by appointment
TA:
Eliyah Afzal
By appointment
All content, lectures, readings, assignments, grades on LMS (and on (except grades).

7. Assessment and Assignments
Reading assignments
Are given for almost every module
Most are background and informational
Some are key to completing assignments
Some are relevant to the current week’s class
Others are relevant to following week’s class (i.e. pre-reading)
Undergraduates - will not be tested on but we will often discuss these in class and participation in these is taken into account
Graduates – are tested as part of assignments, i.e. an extra question
You will progress from individual work to group work

8. ~ Assessment and Assignments#
Type
Topic
Weight
Due Date 1
Individual Written
Use Case and User Requirements Development
10%
Jan 30, 2018 2
Information Uncertainty and Uncertainty Reduction
Feb 13, 2018 3
Analysis of Cognitive, Collection, and Social/Cultural Aspects of Information Systems in Signs
Mar 6, 2018
Individual Presentation 5% 4
Information Models and Information Architectures
Mar 27, 2018 5
Group Written
Development of Use Case, Information Architecture, Model and Prototype Implementation for Informatics Area of Your Choice
20%
Apr 23, 2018
Group Presentation 6
In-Class Individual Participation
Discuss Readings, Lecture Notes, Guest Lectures and Related Informatics’ Current Events in Class
15%
All semester 7
On-line Individual Participation
Answer and discuss on-line questions associated with the weekly Topics

9. Objectives
To instruct future information architects how to sustainably generate information models, designs and architectures
To instruct future technologists how to understand and support essential data and information needs of a wide variety of producers and consumers
For both to know tools, and requirements to properly handle data and information
Will learn and be evaluated on the underpinnings of informatics, including theoretical methods, technologies and best practices.

10. Learning Objectives
Through class lectures, practical sessions, written and oral presentation assignments and projects, students should:
Develop and demonstrate skill in Participation and Organization of multi-skilled teams in the application of Informatics
Demonstrate the development of Conceptual and Information Models and explain them to non-experts (6400 level only)
Demonstrate the application of information theory and design principles to information systems
Evaluate, discuss and be able to apply (6400 level only) Informatics Best Practices and Standards
Demonstrate knowledge (advanced for 6400 level) and application of Informatics Standards
Develop and demonstrate (advanced for 6400 level) skill in Informatics Tool Use and Evaluation 

11. Academic Integrity
Student-teacher relationships are built on trust. For example, students must trust that teachers have made appropriate decisions about the structure and content of the courses they teach, and teachers must trust that the assignments that students turn in are their own. Acts, which violate this trust, undermine the educational process. The Rensselaer Handbook of Student Rights and Responsibilities defines various forms of Academic Dishonesty and you should make yourself familiar with these. In this class, all assignments that are turned in for a grade must represent the student’s own work. In cases where help was received, or teamwork was allowed, a notation on the assignment should indicate your collaboration. If found in violation of the academic dishonesty policy, students may be subject to two types of penalties. The instructor administers an academic (grade) penalty, and the student may also enter the Institute judicial process and be subject to such additional sanctions as: warning, probation, suspension, expulsion, and alternative actions as defined in the current Handbook of Student Rights and Responsibilities. . Submission of any assignment that is in violation of this policy will result in loss of grade for that assignment. If you have any question concerning this policy before submitting an assignment, please ask for clarification.

12. Questions?
Post on LMS
Lectures will be recorded (Adobe Connect) – and posted on LMS
Or send to and

13. Introduction to Informatics
E.g. Bioinformatics
Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological information generated by the scientific community. This deluge of genomic information has, in turn, led to an absolute requirement for computerized databases to store, organize, and index the data and for specialized tools to view and analyze the data.

14. Tell us more…
Bioinformatics is the field of science in which biology, computer science, and information technology merge to form a single discipline.
The ultimate goal of the field is to enable the discovery of new biological insights as well as to create a global perspective from which unifying principles in biology can be discerned.
At the beginning of the "genomic revolution", a bioinformatics concern was the creation and maintenance of a database to store biological information, such as nucleotide and amino acid sequences.
Development of this type of database involved not only design issues but the development of complex interfaces whereby researchers could both access existing data as well as submit new or revised data.

15. And…
Ultimately, however, all of this information must be combined to form a comprehensive picture of normal cellular activities so that researchers may study how these activities are altered in different disease states.
Therefore, the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data, including nucleotide and amino acid sequences, protein domains, and protein structures.

16. And…
The actual process of analyzing and interpreting data is referred to as computational biology. Important sub-disciplines within bioinformatics and computational biology include:
the development and implementation of tools that enable efficient access to, and use and management of, various types of information
the development of new algorithms (mathematical formulas) and statistics with which to assess relationships among members of large data sets, such as methods to locate a gene within a sequence, predict protein structure and/or function, and cluster protein sequences into families of related sequences

17. One result – myexperiment.org

18. Data as Infostructure

19. Definitions
Data - are encodings that represent the qualitative or quantitative attributes of a variable or set of variables.
Data (plural of "datum", which is seldom used) - are typically the results of measurements, computations, or observations and can be the basis of graphs, images of a set of variables.
Data - are often viewed as the lowest level of abstraction from which information and knowledge are derived***
*** we will learn that this is not as simple as it seems.

20. Definitions ctd. Information Knowledge
Representations (of facts? data?) in a form that lends itself to human use
The word information derives from the Latin informare (in+formare) meaning to give form, shape, or character to. It is therefore to be the formative principle of, or to imbue with some specific character or quality.
Knowledge
Check out Wikipedia…. meaning

21. Definitions ctd. Metadata – data about data
Metainformation – information about information
Documentation – integrated collection of information and metadata intended to support all aspects of data (find, access, use…)
Provenance - origin or source from which something comes, intention for use, who/what generated for, manner of manufacture, history of subsequent owners, sense of place and time of manufacture, production or discovery, documented in detail sufficient to allow reproducibility

22. Could it really be this linear?

23. Data-Information-Knowledge Ecosystem
Producers
Consumers
Experience
Data
Information
Knowledge
Creation
Gathering
Presentation
Organization
Integration
Conversation
Context

24. TWC Curriculum tw.rpi.edu/web/Courses
Data Analytics
Producers
Consumers
Data Science
Xinformatics
Semantic eScience
Experience
Data
Information
Knowledge
Creation
Gathering
Presentation
Organization
Integration
Conversation
Context
Web Science

25. The Information Era: Interoperability
Modern information and communications technologies are creating an “interoperable” information era in which ready access to data and information can be truly universal.
Open access to data and services enables us to meet the new challenges of understanding complex systems:
managing and accessing large data sets
higher space/time resolution capabilities
rapid response requirements
data assimilation into models
crossing disciplinary boundaries.
Interoperability technologies have a 20 year history of development and are now mature. Combined with our growing ability to transmit large amounts of information efficiently (Internet, GRID), this provides us with an unprecedented ability to address new and old scientific problems in ways that were hitherto impossible. The challenge now in the geosciences is to capitalise on this new capability. e-Science initiatives are growing up in centers around the world in response to this opportunity.

26. Shifting the Burden from the User to the Provider
In the “heroic” era of science, the provider of data plays a relatively passive role. The onus is on the user to identify each data source, accumulate the required data, and prepare the data for assimilation and analysis. A similar process applies for acquiring software for analysis, modeling, and visualisation. In many cases, the user and the provider are the same person.
In an interoperable e-Science world, the provider has to put much more work into describing the structure and content of data and information, and someone has to provide and support Web Services. The user is relieved of these burdens and benefits accordingly. The overall reduction in work load is enormous, but the provider does not see that.
Fox CI and X-informatics - CSIG 2008, Aug 11

27. Other forms of information
IoT!
Yottabytes

28. Information explosion
Devices are everywhere, but … by 2020

29. And, gulp, ‘un’structured*

30. The key is: As volume, complexity and heterogeneity increase…
Suddenly information may look more like a continuum
All known methods, algorithms will not scale (except for very simple operations)
And because it is information, humans are part of the loop
Thus – we need to understand and apply the theoretical foundations
Problem: most theory to date are developed in an analog world, not a digital one!!

31. Mind the gap
As capabilities and needs grow on both sides: science/ medicine/ engineering – and technology:
There is/ was still a gap between science and the underlying infrastructure and technology that is available
Cyberinfrastructure is the new research environment(s) that support advanced data acquisition, data storage, data management, data integration, data mining, data visualization and other computing and information processing services over the Internet.

32. Mind the gap
As capabilities and needs grow on both sides: science/ medicine/ engineering – and technology:
There is/ was still a gap between science and the underlying infrastructure and technology that is available
Informatics - information science includes the science of (data and) information, the practice of information processing, and the engineering of information systems. Informatics studies the structure, behavior, and interactions of natural and artificial systems that store, process and communicate (data and) information. It also develops its own conceptual and theoretical foundations. Since computers, individuals and organizations all process information, informatics has computational, cognitive and social aspects, including study of the social impact of information technologies. Wikipedia.
Cyberinfrastructure is the new research environment(s) that support advanced data acquisition, data storage, data management, data integration, data mining, data visualization and other computing and information processing services over the Internet.

33. But really it’s not just one field
Informatics IT
Cyber
Infrastructure (CI)
Cyber Informatics
Core Informatics
Science Informatics
Science, Benefit to others
Functional requirements
SBA=societal benefit areas
CI = Discipline neutral, e.g. web server, database, wiki
Cyberinformatics = mapping to discipline neutral aspects
Core informatics = Reasoning engine, semantics, computer science
Science (X) informatics = Use cases, science domain terms, concepts in an ontology or controlled vocabulary

34. A moment of history
In the late 1950’s (actually around or 1962 depending on what you read) the modern informatics term was coined
Existed for a while but then split into library science and computer science and developed their own fields, became disconnected
Now coming back to be relevant to science+…
Informatics IS NOT just having a someone work with an “IT/ICT” person (NOT, NOT, NOT)

35. Cyberinformatics
The first match between the domain and the underlying domain-neutral e-infrastructure/ cyberinfrastructure
When the underlying infrastructure (when it becomes real infrastructure and not just software) changes this is one part that needs to change
Less brittle since upper layers remain intact

36. Core informatics
The realm of computer science (for the most part, also librarians)
Strongly influenced by science (and engineering and medical applications) above and below this layer
If we can leverage this, we do not need to do the specialist work, however …
We must work with these scientists, sustainably

37. Science Informatics
Where science meets the underlying technical capabilities and methods
Must be expressible in science terms; increasingly use cases
The people in this area are multi-lingual and both interdisciplinary and multi-disciplinary, few are trained or literate here ******
Team, or really a community of practice (CoP)

38. Use Case
… is a collection of possible sequences of interactions between the system under discussion and its actors, relating to a particular goal.
The collection should define all system behavior relevant to the actors to assure them goals will be carried out properly.
Any system behavior that is irrelevant to the actors should not be included in the use cases.
is a prose description of a system's behavior when interacting with the outside world.
is a technique for capturing functional requirements of business systems and, potentially, of an IT system to support the business system.
can also capture non-functional
requirements

39. THE PHYSICS OF INFORMATION
BORROMEAN RINGS
Three interlinked circles that represent inseparable parts of the whole. Remove any one ring and the other two fall apart. Because of this property, Borromean Rings have been used as a symbol of unity in many fields.
© 2005 EvREsearch LTD
Courtesy: P Berkman (2005). Remember STRUCTURE!!!!!!!!
Information has three indivisible ingredients – content, context and structure.
The ability to automatically utilize the inherent structure of information is the threshold in information management from hardcopy to digital media.
EvREsearch©

40. Not a perfect story
Many authors criticize the use of the term entropy, and physics of information
Information conservation, diffusion, viscosity, advection, dissipation… sort of all make some sense
Units are a big part of it (question: what are the possible units?) and what are the non-dimensional numbers?
However the idea is very relevant to modeling, design and architecture
We’ll revisit the components of the physics of information

41. Information theory
Semiotics, also called semiotic studies or semiology, is the study of sign processes (semiosis), or signification and communication, signs and symbols, into three branches:
Syntactics: Relation of signs to each other in formal structures
Semantics: Relation between signs and the things to which they refer; their denotata
Pragmatics: Relation of signs to their impacts on those who use them
Wikipedia, see also Peirce:

42. Library science
Curates the artifacts of knowledge but increasingly: (yes) information
Organizes and manages them for consumers
Cataloging and classification
Preservation
‘maintaining or restoring access to artifacts, documents and records through the study, diagnosis, treatment and prevention of decay and damage’ (wikipedia)
In our digital age
Curation and preservation

43. HISTORY OF INFORMATION THRESHOLDS
INFORMATION VOLUME
INFORMATION ERAS
DIGITAL
PAPER
INFORMATION TRANSPORT
INFORMATION INTEGRATION
PAPYRUS
CLAY
Courtesy. Paul Berkman (2005)
STONE
6000
5000
4000
3000
2000
1000
FUTURE
TIME (years before present)
© 2005 EvREsearch LTD

44. ? 5 generations of work and mediation
6th Generation ?
All these generations of mediation are in effect for information systems
From: C. Borgman, 2008, NSF Cyberlearning Report

45. Social Science Branch of humanities
Especially as it relates to networks of people
Exploits sociology of groups, teams
Cultural norms as well as discipline norms
Modes of what and how rewards are given
Between those who produce and those who consume data and information
How you collect, understand, model and design models and architectures is as much social as technical skill

46. Cognitive Science Interdisciplinary study of the mind and intelligence
operates at the intersection of psychology, philosophy, computer science, linguistics, anthropology, and neuroscience.
Of relevance for data and information science are three significant theoretical underpinnings
mental representation,
the nature of expertise,
and intuition
Very relevant to models, modeling, metamodel choice

47. Computer Science Data Structures Knowledge/ Information Representation
Algorithms!! Encoding/ coding
More…

48. Preview of Information Models
Conceptual models, aka domain models, are typically used to explore domain concepts
High-level conceptual models are often created as part of initial requirements envisioning efforts as they are used to explore the high-level static business or science or medicine structures and concepts.
Followed by logical and physical models

49. Object models
An object model is a logic organization of the real world objects (entities), constraints on them, and the relationships among objects. E.g.
A database (DB) language is a concrete syntax for an object (data) model.
A DB system implements that model.

50. Architectures
Building on content, context, and users, some illustrate information architecture as an iceberg.
Just like an iceberg, the majority of information architecture work is out of sight, "below the water."
The work includes the creation of plans, controlled-vocabularies, and blueprints all before any user interfaces are created.

51. Above the water and below
Design, design, design
… of the interfaces… i.e. architecture, of the social, cognitive, etc. elements of information ‘systems’
Almost all are designed to support two basic modes of investigation/ navigation:
induction and deduction… but enough of that for now

52. Information life-cycle (trivial)

53. Visualization

54. Information Audit
Analysis and evaluation of a organization's information system (whether manual or computerized) to detect and rectify blockages, duplication, and leakage of information.
The objectives of this audit are to improve accuracy, relevance, security, and timeliness of the recorded information.
Related to workflow management

55. Information Quality, and Bias
Quality is perceived differently by information providers and information recipients
There are many different qualitative and quantitative aspects of quality
Methodologies for dealing with qualities are just emerging
Little resources are allocated to quality
Each organization handles quality differently
Bias detection is often an expert skill, and bias correction even more-so

56. X=discipline (not eXtreme, sorry)
But really
Core elements that apply across many disciplines

57. Discussion About informatics? Methodology and underpinnings
Definitions? You will hear a LOT of new terms and they are NOT BUZZWORDS – you need to understand them and show me how much
Applications? Software requirement
Components?
Theory (we’ll start on this soon)

58. Skills needed Modeling, theory, architecture experience?
Nah, we’ll cover that
Literacy with computers and applications that can handle information
Yep
Ability to access internet and retrieve/ acquire data
Oh yea
Presentation of assignments
Ditto

59. What is expected
Attend class (ON TIME), complete assignments (esp. reading, be prepared to give comments when asked in subsequent classes)
Participate (e.g. reading), discuss, ask questions
Work constructively in group and class sessions
Work both individually, and then, in a group
USE YOUR RPI ADDRESS
And follow the assignment naming scheme

60. Also on the web
Reading assignments – are intended to prepare you for following lectures and may be considered materials for written assignments or project
Assignments will be posted on LMS
Individual
Group
TA is your first contact for assignment questions but please me/us, seek out office hour appointments, and be engaged

61. What is next
Next week – Capturing the problem: use cases and requirements as-a basis for Assignment 1
Reading for this week - Xinformatics Applications –
Clinical Informatics:
Urban Informatics:
Geo Informatics:
Astro Informatics:
Bio Informatics:
We will discuss these in class next week…